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# Member of Technical Staff, Tech Lead

- **Company:** Listen Labs Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $180,000 - $300,000
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Compilers, Computer Programming, Databases, Intrusion Detection Systems, Microsoft Software, Large Language Models, Backend
- **Published:** October 16, 2026
- **Apply:** https://www.careerbuilder.com/job-details/member-of-technical-staff-tech-lead-san-francisco-ca--33e4895d-301a-4164-b425-c712acd1b6b2

## About the Role

Technical Leadership, Artificial Intelligence (AI), Moderating Skills, Computer Programming, Application Programming Interface (API), Product Development, Entrepreneurship, Startup, Microsoft Product Family, Database Administration

## Description

TL;DR: We're hiring engineers who can build a complex AI-native product on a small team of former founders and top-tier builders., * Database of Humanity. Listen maintains a database of millions of people. We match profiles based on voice, face, and device IDs. Those profiles let us see how opinions change over time, prevent fraud, and find any niche audience.

 * Emotional Intelligence. There's a gap between what people say and what they think. Our AI interviewer reads tone, hesitation, and facial micro-expressions to go beyond the transcript. We've shipped the first version. We're working on surpassing even the best humans.
 * Preference Model. Updating the preference model is a research problem: what we already know, when to refresh it, which questions give the highest signal, and how to quantify the uncertainty in our predictions.
 * Human API. A model of millions of humans is only useful if you can call it from where decisions happen. We want to embed this into Slack, Linear, IDEs, and coding agents themselves. Imagine an agent shipping code, asking Listen what humans actually want, taking action, and iterating.
 * Agent Evals. Every part of our product is built AI-first. Study Composer helps customers scope and design studies. Research Agent analyzes thousands of responses and writes the report. The ceiling is what McKinsey does for $1M per engagement. The bottleneck is evaluating those qualitative outputs. Once you have the eval, you can hill-climb.

Who You Are

 * You solve problems end to end. The team is split vertically, so every engineer owns a part of the product and makes decisions across the LLM pipeline, infrastructure, backend, and UX.
 * You're a future or past founder. You scope your own work, think about the customers, and own your decisions.
 * You care about getting things right. Moving fast is essential, but a 100% solution is much more powerful than an 80% one. When something breaks, you go to root cause.
 * You're excited about pushing LLMs to their limits. We work directly with the frontier model labs on new releases and constantly probe where they break.
 * You communicate complex ideas in writing. We work independently with one meeting a week, so writing is how tradeoffs, problems, and decisions get worked through together.
 * You're highly technical. Most of our team started coding as teenagers and nerd out on details from language design to compilers.